Existing Terminology and Artificial Intelligence Terminology
By Sue Ellson
I remember my grandmother saying that she ‘never uses a computer’ as she went to pay for her groceries at the supermarket with a plastic card. Technology is so ubiquitous that we can almost no longer ‘see’ it in our daily lives.
One of the first forms of ‘artificial intelligence’ that comes to my mind is predictive text on my mobile phone. When it first started, it was pretty average – and in fact, so bad that I turned it off!
I feel a bit the same way about some of the new artificial intelligence AI technology we are dealing with now. I am finding the ongoing improvements to Microsoft’s Copilot fascinating.
For anyone who is still living in 2023, we need to understand new terminology and consider how we can use it to our advantage.
We also need to move beyond a ‘faster horse’ and towards ‘a motor vehicle’ in our overall approach to the rapid rate of technological change.
Personally, I believe that if we do not keep up to date with this terminology and the principles of its application, we will be left behind the people who can use it effectively.
I will talk more about this topic in the future, but for now, I would just like to guide you with a warm introduction to some of the technological terms you may like to learn in relation to what you already know now.
On the left column, the existing terminology you may know now.
On the right column, the AI terminology you need to know now.
| Existing Terminology | AI Terminology |
|---|---|
| Databases – a database is an organized collection of data stored and accessed electronically through the use of a database management system * remember garbage in garbage out and aim for a single source of truth (not multiple single use spreadsheets) | Dataset – is a collection of data. In the case of tabular data, a data set corresponds to one or more database tables, where every column of a table represents a particular variable, and each row corresponds to a given record of the data set in question * much larger amount of information that can be queried in more ways |
| Query Language – also known as data query language or database query language, is a computer language used to make queries in databases and information systems. A well known example is the Structured Query Language (SQL) * enables you to create a query to get the results you need | Prompt – prompt is natural language text describing the task that an AI should perform * many ‘chat prompts’ that are being recommended to help you get the results you need – the better the prompt, the better the response |
| Algorithm – is a finite sequence of rigorous instructions, typically used to solve a class of specific problems or to perform a computation * based on multiple factors and often changed by a platform to meet their ‘megalomaniac’ needs, not the consumer’s needs ** megalomaniac – more people, more often, more time (applies to search engines and social media platforms) | Machine Learning – umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machines ‘discover’ their ‘own’ algorithms without needing to be explicitly told what to do by any human-developed algorithms * beware those that don’t follow important rules and create unintended consequences like biases towards certain outcomes (ie Western English dataset not aware of cultural nuance) |
| Internet or Website Browser – A web browser is an application for accessing websites. When a user requests a web page from a particular website, the browser retrieves its files from a web server and then displays the page on the user’s screen. Browsers are used on a range of devices, including desktops, laptops, tablets, and smartphones * need digital asset value and digital currency value via continuous contributions | App – an application, especially as downloaded by a user to a mobile device * allows people to complete tasks within a ‘closed’ environment’ and not leave the app to go back to a web browser search e.g. People using a search on TikTok or YouTube rather than going to online search and getting a result from there |
| Web Browser Extension – a software module for customizing an internet website browser * be selective as they can collect or mine data and conflict with other extensions | Chatbots – a software application or web interface that aims to mimic human conversation through text or voice interactions * can learn over time but beware if operated by a third party (ie Facebook) |
| Search Engine Results Pages SERPs – The page that a search engine returns after a user submits a search query. In addition to organic search results, search engine results pages (SERPs) usually include paid search and pay-per-click (PPC) ads * need to adapt to changing algorithms | Chat Experience Results Page CHERPs – the generative AI result you see after you enter a prompt on Google (Google Gemini), Microsoft Bing, ChatGPT or any other generative AI platform * based on large datasets, more likely to include website content and not include every piece of your social media content – publish on your website first! |
| Predictive Text – is an input technology that facilitates typing on a device by suggesting words the user may wish to insert in a text field * relies on regular use phrasing and can ‘dumb down’ language but learns what you use regularly | Embedded Artificial Intelligence is the application of machine and deep learning in software that can be programmed to provide both predictive and reactive intelligence, based on the data that is collected and analysed * relies on quality of datasets and programming used and it can ‘learn’ your style preferences over time (and likes emotional language – please, thank you) |
| Universal Design – the design of buildings, products or environments that is done in a way to make them accessible to people, regardless of age, disability or other factors * viewed on the basis of accessibility after creation | Design for All – ensures that everything that is designed and made is accessible, convenient for everyone in society to use and responsive to evolving human diversity * whilst a feature may be designed for someone with a disability, it helps everyone use it more effectively e.g. voice to text |
Some New Terminology
Large Language Model (LLM) is a language model characterized by its large size. Their size is enabled by AI accelerators, which are able to process vast amounts of text data, mostly scraped from the Internet. It doesn’t rely on a weighted algorithm pre-prepared database.
Natural Language Processing (NLP) is an interdisciplinary subfield of linguistics and computer science. It is primarily concerned with processing natural language datasets, such as text corpora or speech corpora, using either rule-based or probabilistic machine learning approaches. It doesn’t rely on a weighted algorithm to provide a result.
Generative Artificial Intelligence is artificial intelligence capable of generating text, images, or other media, using generative models. Generative AI models learn the patterns and structure of their input training data and then generate new data that has similar characteristics. You are asking the AI to do something for you.
Regenerative AI systems continuously learn, adapt, and improve based on feedback, making them highly resilient and responsive however, they may learn on the ‘wrong’ information and most of your work is ‘tracked’ and you need to be signed in. Essentially, you start with a Generative AI result and then you can choose to Regenerate either automatically or with further instructions.
Bias Machine Learning bias, also known as Algorithm bias or AI bias, is a phenomenon that occurs when an algorithm produces results that are systemically prejudiced due to erroneous assumptions in the machine learning (ML) process.
I hope you find this information helpful and please contact me directly for more insights!